Upload folder using huggingface_hub

app/pages.py

@@ -173,23 +173,21 @@ def general_reasoning():
                          'ZBench': 'zbench', 
                          'IndoMMLU': 'indommlu'}
 
-    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    left, center, middle, _, right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
     with left:
         category_one = st.selectbox('Zero or Few Shot', filters_levelone)
     with center:
         category_two = st.selectbox('Dataset', filters_leveltwo)
-    
-    # with right:
-    #     sortby = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    with middle:
+        model_size_range = st.selectbox('Model Size', ['All', '<10B', '10B-30B', '>30B'])
     
     sortby = 'Ascending'
 
     if category_one or category_two or sortby:
         category_one = category_one_dict[category_one]
         category_two = category_two_dict[category_two]
-        draw('general_reasoning', category_one, category_two, 'Accuracy',sortby)
-    # else:
-    #     draw_only_acc('general_reasoning', 'zero_shot', 'MMLU Full', 'Descending')
+        draw('general_reasoning', category_one, category_two, 'Accuracy', sortby, model_size_range)
+
 
 def flores():
     st.title("Task: FLORES-Translation")
@@ -209,22 +207,21 @@ def flores():
                          'Malay to English': 'zsm2eng'}
     
 
-    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    left, center, middle, _, right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
     with left:
         category_one = st.selectbox('Zero or Few Shot', filters_levelone)
     with center:
         category_two = st.selectbox('Dataset', filters_leveltwo)
-    # with right:
-    #     sortby = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    with middle:
+        model_size_range = st.selectbox('Model Size', ['All', '<10B', '10B-30B', '>30B'])
 
     sortby = 'Ascending'
 
     if category_one or category_two or sortby:
         category_one = category_one_dict[category_one]
         category_two = category_two_dict[category_two]
-        draw('flores_translation', category_one, category_two, 'BLEU',sortby)
-    # else:
-    #     draw_flores_translation('zero_shot', 'Indonesian to English', 'Descending')
+        draw('flores_translation', category_one, category_two, 'BLEU', sortby, model_size_range)
+
 
 def emotion():
     st.title("Task: Emotion")
@@ -240,23 +237,21 @@ def emotion():
     category_two_dict = {'Indonesian Emotion  Classification': 'ind_emotion', 
                              'SST2': 'sst2'}
 
-    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    left, center, middle, _, right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
     with left:
         category_one = st.selectbox('Zero or Few Shot', filters_levelone)
     with center:
         category_two = st.selectbox('Dataset', filters_leveltwo)
-    # with right:
-    #    sortby = st.selectbox('sorted by', ['Ascending', 'Descending'])
-
+    with middle:
+        model_size_range = st.selectbox('Model Size', ['All', '<10B', '10B-30B', '>30B'])
+    
     sortby = 'Ascending'
 
 
     if category_one or category_two or sortby:
         category_one = category_one_dict[category_one]
         category_two = category_two_dict[category_two]
-        draw('emotion', category_one, category_two, 'Accuracy', sortby)
-    # else:
-    #     draw_only_acc('emotion', 'zero_shot', 'Indonesian Emotion  Classification', 'Descending')
+        draw('emotion', category_one, category_two, 'Accuracy', sortby, model_size_range)
 
 def dialogue():
     st.title("Task: Dialogue")
@@ -274,29 +269,27 @@ def dialogue():
                          'SAMSum': 'samsum', 
                          'DialogSum': 'dialogsum'}
 
-    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
+    left, center, middle, _, right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
     with left:
         category_one = st.selectbox('Zero or Few Shot', filters_levelone)
     with center:
         category_two = st.selectbox('Dataset', filters_leveltwo)
-    with middle:
+    with right:
         if category_two == 'DREAM':
             sort = st.selectbox('Sort', ['Accuracy'])
         else:
             sort = st.selectbox('Sort', ['Average', 'ROUGE-1', 'ROUGE-2', 'ROUGE-L'])
-    
-    #with right:
-    #    sortby = st.selectbox('by', ['Ascending', 'Descending'])
 
+    with middle:
+        model_size_range = st.selectbox('Model Size', ['All', '<10B', '10B-30B', '>30B'])
+    
     sortby = 'Ascending'
 
-
     if category_one or category_two or sort or sortby:
         category_one = category_one_dict[category_one]
         category_two = category_two_dict[category_two]
-        draw('dialogue', category_one, category_two, sort, sortby)
-    # else:
-    #     draw_dialogue('zero_shot', 'DREAM', sort[0],'Descending')
+        draw('dialogue', category_one, category_two, sort, sortby, model_size_range)
+
 
 def fundamental_nlp_tasks():
     st.title("Task: Fundamental NLP Tasks")
@@ -316,20 +309,17 @@ def fundamental_nlp_tasks():
                         'RTE': 'rte', 
                         'MRPC': 'mrpc'}
 
-    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    left, center, middle, _, right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
     with left:
         category_one = st.selectbox('Zero or Few Shot', filters_levelone)
     with center:
         category_two = st.selectbox('Dataset', filters_leveltwo)
-    
-    # with right:
-    #    sortby = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    with middle:
+        model_size_range = st.selectbox('Model Size', ['All', '<10B', '10B-30B', '>30B'])
     
     sortby = 'Ascending'
 
     if category_one or category_two or sortby:
         category_one = category_one_dict[category_one]
         category_two = category_two_dict[category_two]
-        draw('fundamental_nlp_tasks', category_one, category_two, 'Accuracy', sortby)
-    # else:
-    #     draw_only_acc('fundamental_nlp_tasks', 'zero_shot', 'OCNLI', 'Descending')
+        draw('fundamental_nlp_tasks', category_one, category_two, 'Accuracy', sortby, model_size_range)